| YANG Jiaqiang(杨家强),QIN Danyang,TANG Huapeng,TAO Sili.[J].高技术通讯(英文),2025,31(2):184~193 |
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| A visual indoor positioning method with pedestrian interference suppression |
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| DOI：10. 3772 / j. issn. 1006-6748. 2025. 02. 008 |
| 中文关键词: |
| 英文关键词: visual positioning, disturbance of pedestrians, image retrieval |
| 基金项目: |
| Author Name | Affiliation | | YANG Jiaqiang(杨家强) | (College of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R. China)
(National Mobile Communications Research Laboratory , Southeast University , Nanjing 210096 , P. R. China) | | QIN Danyang | | | TANG Huapeng | | | TAO Sili | |
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| 中文摘要: |
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| 英文摘要: |
| Visual indoor positioning methods have the potential for widespread application in complex large-scale indoor environments, such as shopping centers and hospitals. However, during the visual positioning process, passing pedestrians may cause occlusion in the visual image, leading to large deviations in the visual positioning results. Aiming at the problem of feature occlusion in visual images caused by pedestrians, this paper proposes a visual indoor positioning system that combines semantic segmentation and image restoration. The paper proposes a method called the fast image segmentation repair (FISR), which segments and rapidly repairs the selected image to eliminate the influence of pedestrians on image feature extraction and improve positioning accuracy. In addition, the paper proposes a method called local feature based bag-of-visual-words combined with high-level semantic information ( LFHS) for image retrieval. LFHS uses both local features and high-level semantic information to obtain more comprehensive and accurate representations of image features.This approach improves the accuracy and robustness of image retrieval by harnessing the combined power of local features and high-level semantic information. Experimental results show that the proposed positioning method reduces the average positioning error by 0. 35 m compared with NetVLAD and 0. 49 m compared with MixVPR, significantly improving the performance of visual positioning technology. |
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